Package: multisite.accuracy
Type: Package
Title: Estimation of Accuracy in Multisite Machine-Learning Models
Version: 1.3
Date: 2024-07-31
Authors@R: person(given = "Joaquim", family = "Radua", email = "quimradua@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-1240-5438"))
Description: The effects of the site may severely bias the accuracy of
        a multisite machine-learning model, even if the analysts
        removed them when fitting the model in the 'training set' and
        applying the model in the 'test set' (Solanes et al.,
        Neuroimage 2023, 265:119800). This simple R package estimates
        the accuracy of a multisite machine-learning model unbiasedly,
        as described in (Solanes et al., Psychiatry Research:
        Neuroimaging 2021, 314:111313). It currently supports the
        estimation of sensitivity, specificity, balanced accuracy (for
        binary or multinomial variables), the area under the curve,
        correlation, mean squarer error, and hazard ratio for binomial,
        multinomial, gaussian, and survival (time-to-event) outcomes.
License: GPL-3
Imports: coxme, lme4, lmerTest, logistf, metafor, pROC, survival
NeedsCompilation: no
Packaged: 2026-07-20 06:15:54 UTC; root
Author: Joaquim Radua [aut, cre]
        (<https://orcid.org/0000-0003-1240-5438>)
Maintainer: Joaquim Radua <quimradua@gmail.com>
Config/pak/sysreqs: cmake make libicu-dev libx11-dev zlib1g-dev
Repository: https://jrad1.r-universe.dev
Date/Publication: 2024-08-01 02:50:19 UTC
RemoteUrl: https://github.com/cran/multisite.accuracy
RemoteRef: HEAD
RemoteSha: d20a679cf8dc5e1b6c73121309ca360aaffcbcd9